PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Metoda analizy widm mierzonych z wykorzystaniem spektrometrów OP-FTIR w monitorowaniu powietrza atmosferycznego oraz gazów w procesach przemysłowych

Treść / Zawartość
Identyfikatory
Warianty tytułu
EN
Open Path FT-IR Spectra Analysis Method for Monitoring of Environment and Processes with Varying Conditions
Języki publikacji
PL
Abstrakty
EN
Open-Path Fourier Transform Infrared (OP-FTIR) can be used for monitoring of atmospheric environment. The open path technique is based on the measurement of the absorption along the atmosphere path between radiation source and spectrometer. Measurement paths used in this method have a considerable length – from tens of meters to several kilometers. The main advantage of OP-FTIR spectrometry is the possibility of continuously and simultaneously measuring concentrations of multiple compounds. Unfortunately, quantitative analysis of the spectra of such measurements is a difficult issue due to the changing atmospheric conditions and overlapping of the absorption spectra of various components. Numerous algorithms used for the interpretation of the measured spectra have been proposed. They can be classified into methods using classical chemometric calibration and iterative algorithms. Classical Least Square CLS and Partial Least Square PLS are the most commonly used methods of OP-FTIR spectrometry. Iterative methods are based on comparing measured data with synthetic spectra, that is computational models of investigated optical path transmission. For this purpose, databases such as HITRAN are used. Transmission model must take into account not only the spectral characteristics of gases, but also the measuring instrument influence on the measured spectrum. As an example of modeling the spectra of NH3 and HCl gas are used. Modeling of gas spectra with different resolution is shown. Classical methods of building a chemometric calibration model require appropriate reference samples. This is usually associated with considerable cost and time-consuming calibration process. In addition, correct calibration requires maintaining the same conditions during the calibration, as in practical measurements. This is possible only in the case of laboratory measurements. In particular, it is necessary to maintain a constant temperature and pressure of examined substances. It is connected with changes in width and intensity of gas rotational lines. In classical spectroscopy, changing environmental conditions require new calibration measurements. In the open path spectroscopy, changes in conditions occur naturally along with the changes in the examined environment (object, process). If the measurement conditions in the environment differ from those in calibration measurements, significant errors in determining the content of the ingredients may appear. Greater changes in conditions may occur in a variety of chemical or physical processes. Sometimes it is not possible to perform measurements in conditions similar to those occurring in a particular industrial facility. In such cases, synthetic spectra may be used in two ways: in an iterative process to compare with measured spectra or to form a chemometric calibration models. In the latter case, the problem of changing conditions can be solved in several ways. The simplest method is to build separate calibration models for all conditions that can occur during the measurement. However, in order to use this method, it is necessary to measure the existing conditions and choose an appropriate local model. Another method is to correct the measured spectra and to adapt them to the standard conditions. The third option is to build global models. The spectra of all the conditions that may occur during the measurement are then used for building a calibration model. Then, the effect of temperature on the determination of gas content for local calibration models is investigated. Finally, a global calibration model insensitive to temperature changes in 10-40°C range is built.
Rocznik
Strony
218--234
Opis fizyczny
Bibliogr. 28 poz., rys.
Twórcy
  • Lublin University of Technology
autor
  • Lublin University of Technology
autor
  • Al-Farabi Kazakh National University
  • Lublin University of Technology
Bibliografia
  • 1. Arsic, D., Milovanovic, D. R., Jevtovic, I., Vlajkovic, V., Arsic, K. (2014). Using a Mobile Multigas FTIR Analyzer in Four Different Environmental Accidents. Polish Journal of Environmental Studies, 23(5), 1483-1489.
  • 2. Bacsik, Z., Komlósi, V., Ollar, T., Mink, J. (2006). Comparison of Open Path and Extractive Long-Path FTIR Techniques in Detection of Air Pollutants. Applied Spectroscopy Reviews, 41, 77-97.
  • 3. Bjorneberg, D. L., Leytem, A. B., Westermann, D. T., Griffiths, P. R., Shao, L., Pollard, M. J. (2009). Measurement of Atmospheric Ammonia, methane, and Nitrous Oxide at a Concentrated Dairy Production Facility in Southern Idaho Using Open-Path FTIR Spectrometry. Transaction of ASABE, 52(5), 1749-1756.
  • 4. Borkowski, J., Mroczka, J. (2010) LIDFT method with classic data windows and zero padding in multifrequency signal analysis. Measurement, 43, 1595-1602.
  • 5. Cięszczyk, S. (2014). Influence of temperature on synthetic data-based calibration models for low resolution open-path FTIR spectroscopy. Bulletin of the Polish Academy of Sciences Technical Sciences, 62(1), 33-42.
  • 6. Daszykowski, M., Serneels, S., Kaczmarek, K., Van Espen, P., Croux, C., Walczak, B. (2007). TOMCAT: A MATLAB toolbox for multivariate calibration techniques. Chemometrics and Intelligent Laboratory Systems, 85, 269-277.
  • 7. Ferguson, F.T., Johnson, N.M., Nuth, III J.A. (2015). On the Use of Fourier Transform Infrared (FT_IR) Spectroscopy and Synthetic Calibration Spectra to Quantify Gas Concentrations in a Fisher-Tropsch Catalyst System. Applied Spectroscopy, 69(10), 1157-1169.
  • 8. Flores, E., Viallon, J., Moussay, P., Wielgosz, R. I. (2013). Accurate Fourier Transform Infrared (FT-IR) Spectroscopy measurements of Nitrogen Dioxide (NO2) and Nitric Acid (HNO2) Calibrated with Synthetic Spectra. Applied Spectroscopy, 67(10),1171-1178.
  • 9. Griffith, D.W.T. (1996). Synthetic Calibration and Quantitative Analysis of GasPhase FT-IR Spectra. Applied Spectroscopy, 50(1), 59-70.
  • 10. Griffith, D.W.T., Deutscher, N., Caldow, C., Kettlewell, G., Riggenbach, M., Hammer S. (2012). A Fourier transform infrared trace gas and isotope analyser for atmospheric applications. Atmospheric Measurement Techniques, 5, 2481-2498.
  • 11. Heise, H.M., Muller, U., Gartner, A.G., Hoischer, N. (2001). Improved Chemometric Strategies for Quantitative FTIR Spectral Anslysis and Applications in Atmospheric Open-Path Monitoring. Field Analytical Chemistry and Technology, 5(1-2), 13-28.
  • 12. Kim, M. T., Song, S., Yim, Y.J., Jang, M.W., Baek, G. (2015). Comparative Study on Infrared Irradiance Emitted from Standard and Real Rocket Motor Plumes. Propellants, Explosives, Pyrotechnics, 40, 779-785.
  • 13. Leytem, A. B., Dungan, R. S., Bjorneberg, D. L., Koehn, A.C. (2013). Greenhouse Gas and Ammonia Emissions from Open-Freestall Dairy in Southern Idaho. Journal of Environmental Quality, 42, 10-20.
  • 14. Li, Y., Wang, J. (2003). The Real Time Diagnostics of Combustion Characteristics of Solid Propellant by Remote Sensing FTIR System. Instrumentation Science & Technology, 31(1), 33-45.
  • 15. Lin, C., Liou, N., Sun E. (2008). Applications of Open-Path Fourier Transform Infrared for Identification of Volatile Organic Compound Pollution Sources and Characterization of Source Emission Behaviors. Journal of Air & Waste Management Association, 58, 821-828.
  • 16. Morrison, P.W., Taweechokesupsin, O. (1998). Calculation of Gas Spectra for Quantitative Fourier Transform Infared Spectroscopy of Chemical Vapor Deposition. J. Electrochem. Soc., 145(9), 3212-3219.
  • 17. Moore, K.D., Young, E., Gurell, C., Wojcik, M.D., Martin, R.S., Bingham, G.E., Pfeiffer, R.L., Prueger, J.H, Hargield, J.L. (2014). Ammonia Measurement and Emissions from a California Dairy Using Point and Remote Sensors. Transactions of the ASABE, 57(1), 181-198.
  • 18. Muller, U., Heise, H.M., (2001). Reliable Component Identification in Atmospheric Open-Path FTIR Spectroscopy by a Cross-Correlation Method. Field Analytical Chemistry and Technology, 5, 50-59.
  • 19. Reiche, N., Westerkamp, T., Lau, S., Borsdorf, H., Dietrich, P., Schutze, C. (2014). Comparative study to evaluate three ground-based optical remote sensing techniques under field conditions by a gas tracer experiment. Environ Earth Science, 72, 1435-1441.
  • 20. Ren, Y., Li, Y., Yu, B., Wang, J., Hu, L. (2007). Combination of Neural Network and SBFM Algorithm for Monitoring VOCs Distribution by Open Path FTIR Spectrometry. Instrumentation Science and Technology, 35, 1-14.
  • 21. Risø National Laboratory for Sustainable Energy, Technical University of Denmark (2012). http://130.226.56.153/ofd/ftir/downloads.htm (dostęp 01.2012).
  • 22. Ross, K. R., Todd, L. A. (2002). Field Evaluation of a Transportable Open-Path FTIR Spectrometer for Real-Time Air Monitoring. Applied Occupational and Environmental Hygiene, 17(2), 131-143.
  • 23. Rothman, L.S., Gordon, I.E., Barbe, A., Benner, D. C., Bernath, P.F., Birk, M., Boudon, V., Brown, L.R., Campargue, A., Champion, J.-P., Chance, K., Coudert, L.H., Dana, V., Devi, V.M., Fally, S., Flaud, J.-M., Gamache, R.R., Goldman, A., Jacquemar,t D., Kleiner, I., Lacome, N., Lafferty, W.J., Mandin, J.-Y., Massie, S.T., Mikhailenko, S.N., Miller, C.E., Moazzen-Ahmadi, N., Naumenko, O.V., Nikitin, A.V., Orphal, J., Perevalov, V.I., Perrin, A., Predoi-Cross, A., Rinsland, C.P., Rotger, M., Simeckova, M., Smith, M.A.H., Sung. K., Tashkun, S.A., Tennyson. J., Toth, R.A., Vandaele, A.C., Auwera, J. V. (2009). The HITRAN 2008 molecular spectro- scopic database. Journal of Quantitative Spectroscopy & Radiative Trans- fer, 110, 533-572.
  • 24. Rothman, L.S., Rinsland, C.P., Goldman, A., Massie, S.T., Edwars, D.P., Flaud, J.-M., Perrin, A., Camy-Peyret, C., Dana, V., Mandin, J.-Y., Schroeder, J., Mccann, A., Gamache, R.R., Wattson, R.B., Yoshino, K., Chance, K.V., Jucks, K.W., Brown, L.R., Nemtchinov, V., Varanasi, P. (1998). The HI- TRAN molecular spectroscopic database and HAWKS (HITRAN atmospheric workstation): 1996 edition. Journal of Quantitative Spectroscopy &Radiative Transfer, 60(5), 665-710.
  • 25. Shao, L., Griffiths, P.R., Chu, P. M., Vetter, T. W. (2006). Quantitative Vapor- Phase Infrared Spectrometry of Ammonia. Applied Spectroscopy, 60(3), 254-260.
  • 26. Shao, L., Griffiths, P.R., Leytem, A.B. (2010). Advances in Data Processing for Open-Path Fourier Transform Infrared Spectrometry of Greenhouse Gases. Analytical Chemistry, 82(19), 8027-8033.
  • 27. Shao, L., Liu, B., Griffiths, P.R., Leytem, A.B. (2011). Using Multiple Calibration Sets to Improve the Quantitative Accuracy of Partial Least Squares (PLS) Regression on Open-Path Fourier Transform Infrared (OP/FT-IR) Spectra of Ammonia over Wide Concentration Ranges. Applied Spectro- scopy, 65(7), 820-824.
  • 28. Schutze, C., Lau, S., Reiche, N., Sauer, U., Borsdorf H., Dietrich, P. (2013).Ground-Based Remote Sensing with Open-Path Fourier-Transform Infrared (OP-FTIR) Spectroscopy for Large-Scale Monitoring of Greenhouse Gases. Energy Procedia, 37, 4276-4282.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-718b45ad-e540-4c95-a831-1f135060bca9
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.